{"title":"Identifying reliable obesity indices for hyperuricemia among middle-aged and elderly populations: a longitudinal study.","authors":"Yuntong Liu, Wei Zhao, Xuhan Liu, Haodong Jiang, Yixia Wu, Lan Luo, Zhengnan Gao","doi":"10.1186/s12944-024-02296-6","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Given the established link between obesity and hyperuricemia (HUA), the research want to investigate the relationship between different obesity indices and HUA, and further analyze which obesity index can better predict HUA.</p><p><strong>Methods: </strong>The data were obtained from a longitudinal study involving middle-aged and elderly populations in Dalian, China. The research encompassed individuals who exhibited typical uric acid levels initially and tracked their progress over a three-year period. 8 obesity indices were evaluated retrospectively. Subgroup analyses were conducted to identify susceptible populations. Restricted cubic splines (RCS) were utilized to model the dose-response relationships between obesity indices and HUA. Receiver operating characteristic (ROC) curves were applied to visualize and compare the predictive value of both traditional and new obesity indices for HUA.</p><p><strong>Results: </strong>Among 4,112 individuals with normal baseline uric acid levels, 950 developed HUA. Significant associations with HUA were observed for body mass index (BMI), waist circumference (WC), body roundness index (BRI), cardiometabolic index (CMI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), and abdominal volume index (AVI). Subgroup analysis indicated that all obesity indices proved more effective in assessing the onset of HUA in women without Metabolic Syndrome (MetS). Further analysis using RCS revealed non-linear dose-response relationships between LAP, CMI, VAI, and HUA in males, with similar non-linear relationships observed for all indices in females. The results from the ROC curves indicate that LAP may serve as a better predictor of HUA in males, and CVAI may serve as a better predictor in females.</p><p><strong>Conclusion: </strong>HUA is closely associated with obesity indices. Among females, CVAI emerges as the preferred predictive index for HUA. In males, LAP emerges as the preferred predictive index for HUA.</p>","PeriodicalId":18073,"journal":{"name":"Lipids in Health and Disease","volume":"23 1","pages":"305"},"PeriodicalIF":3.9000,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11426091/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Lipids in Health and Disease","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12944-024-02296-6","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Given the established link between obesity and hyperuricemia (HUA), the research want to investigate the relationship between different obesity indices and HUA, and further analyze which obesity index can better predict HUA.
Methods: The data were obtained from a longitudinal study involving middle-aged and elderly populations in Dalian, China. The research encompassed individuals who exhibited typical uric acid levels initially and tracked their progress over a three-year period. 8 obesity indices were evaluated retrospectively. Subgroup analyses were conducted to identify susceptible populations. Restricted cubic splines (RCS) were utilized to model the dose-response relationships between obesity indices and HUA. Receiver operating characteristic (ROC) curves were applied to visualize and compare the predictive value of both traditional and new obesity indices for HUA.
Results: Among 4,112 individuals with normal baseline uric acid levels, 950 developed HUA. Significant associations with HUA were observed for body mass index (BMI), waist circumference (WC), body roundness index (BRI), cardiometabolic index (CMI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), and abdominal volume index (AVI). Subgroup analysis indicated that all obesity indices proved more effective in assessing the onset of HUA in women without Metabolic Syndrome (MetS). Further analysis using RCS revealed non-linear dose-response relationships between LAP, CMI, VAI, and HUA in males, with similar non-linear relationships observed for all indices in females. The results from the ROC curves indicate that LAP may serve as a better predictor of HUA in males, and CVAI may serve as a better predictor in females.
Conclusion: HUA is closely associated with obesity indices. Among females, CVAI emerges as the preferred predictive index for HUA. In males, LAP emerges as the preferred predictive index for HUA.
期刊介绍：
Lipids in Health and Disease is an open access, peer-reviewed, journal that publishes articles on all aspects of lipids: their biochemistry, pharmacology, toxicology, role in health and disease, and the synthesis of new lipid compounds.
Lipids in Health and Disease is aimed at all scientists, health professionals and physicians interested in the area of lipids. Lipids are defined here in their broadest sense, to include: cholesterol, essential fatty acids, saturated fatty acids, phospholipids, inositol lipids, second messenger lipids, enzymes and synthetic machinery that is involved in the metabolism of various lipids in the cells and tissues, and also various aspects of lipid transport, etc. In addition, the journal also publishes research that investigates and defines the role of lipids in various physiological processes, pathology and disease. In particular, the journal aims to bridge the gap between the bench and the clinic by publishing articles that are particularly relevant to human diseases and the role of lipids in the management of various diseases.
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